RESTRICTED only accessable in CEN/MPI network or via CliSAP login What does that mean?
The WindSat sensor aboard the Coriolis satellite has been the first satellite passive microwave sensor measuring the full stokes vector (at 37 GHz). This allows to retrieve the wind speed AND the wind direction over the ice-free ocean surface - the main products of this satellite sensor. In addition the multi-frequency, multi-polarization capability of this sensor (6.8 GHz, 10.7 GHz, 18.7 GHz, 23.8 GHz, 37.0 GHz) allows to further optimize the wind speed retrieval by contemporary measurements of parameters influencing this retrieval such as the sea surface temperature (SST), columnar values of the water vapor and the cloud liquid water content, and the rain rate (similar to, e.g. SSM/I used for the HOAPS data set).
Remote Sensing Systems (REMSS, http://www.remss.com) used WindSat data to compute the surface wind vector at 10 m height above the ocean surface. To do so various channel combinations are used. Here we only offer the all-weather wind speed product which comes at a somewhat coarser spatial resolution but is basically independent of rain effects. We refer to data set web page at REMSS: http://www.remss.com/missions/windsat and the references section for details.
The product offered here is a modified version of the daily WindSat ocean surface wind vector product v07.0.1 obtained from REMSS in early September 2015. The modification applied by ICDC is the conversion from flat binary into netCDF file format, and the computation of the u- and v-wind vector components from wind speed and direction.
Last data set update at ICDC: August 20, 2020.
|wind speed||m/s||all variables separately for ascending and descending overpasses||39km x 71km (under rain); 25km x 38km (else)|
|wind direction||degrees (0 ... 360°)||direction into which the wind blows||25km x 38km|
|u-component||m/s||-50 ... 50||39km x 71km (under rain); 25km x 38km (else)|
|v-component||m/s||-50 ... 50||39km x 71km (under rain); 25km x 38km (else)|
|rain rate||mm/h||0 ... 25||8km x 13km|
|sea surface temperature (SST)||degC||-3 ... 34.5||39km x 71km|
|columnar water vapor content||kg/m²||0 ... 75||16km x 27km|
|columnar cloud liquid water content||kg/m²||0 ... 2.45||16km x 27km|
|decimal time||hours since 0 UTC||each swath pair has different overpass time||--|
Period and temporal resolution:
- 2003-02-05 to 2020-06-30
- Daily (2 times, ascending & descending overpasses)
Missing days: Aug. 9-11 2017, Jan. 10-13 2019
Coverage and spatial resolution:
- Global, over open water
- Spatial resolution: 0.25° x 0.25°, cartesian grid
- Geographic longitude: 0°E to 360°E
- Geographic latitude: -90°N to 90°N
- Dimension: 1440 columns x 720 rows
- Altitude: 0.0 m
The data set offered here does not include any explicit uncertainty estimations.
The antenna temperatures measured by the sensor from the fore and aft looking directions are processed into top-of-the-atmosphere brightness temperatures (TBs) and inter-calibrated with other satellite passive microwave instruments (see GMI_ATBD (pdf, not barrier-free)).
The product comes at 0.25° grid resolution. However, the effective resolution of the product depends on the footprint size of the sensors' channels used. All products which are using TBs from the 6.8 GHz channels with the coarsest spatial resolution have the corresponding effective spatial resolution which is given in a separate column in the table under parameters.
The advantage of a multi-frequency, multi-polarization instrument like WindSat is that contributions from atmospheric parameters such as water vapor, cloud liquid water and rain can be directly estimated from the same set of TBs (similar to what is done from SSM/I data for the HOAPS data set) which helps to optimize the wind speed and also wind direction retrieval. High values in any of these three parameters might still deteriorate the wind vector retrieval. In particular the wind direction retrieval using WindSat is hampered by rain rates above 15 mm/hour. Note further that wind direction cannot be retrieved under wind speeds below 3 m/s.
The capability of WindSat to measure TBs at 6.8 GHz and 10.7 GHz also allows to retrieve the SST which also helps to optimize the wind vector retrieval. At the same time, however, RFI and sun glint effect the TBs at these low-frequency channels and the SST retrieval and therefore also the wind vector retrieval; affected grid cells are flagged accordingly.
All above-mentioned parameters retrieved from WindSat data are included in the data set.
We refer to the section references for further information.
Remote Sensing Systems
Santa Rosa, CA, U.S.A.
email: support (at) remss.com
ICDC / CEN / University of Hamburg
email: stefan.kern (at) uni-hamburg.de
- REMSS Data User Guide
- Meissner, T., and F. J. Wentz (2012), The emissivity of the ocean surface between 6 - 90 GHz over a large range of wind speeds and Earth incidence angles, Transactions Geoscience Remote Sensing, 50(8), 3004-3026. (not barrier-free)
- Meissner, T., L. Ricciardulli, and F. J. Wentz (2011), All-weather wind vector measurements from intercalibrated active and passive microwave satellite sensors, paper presented at 2011 IGARSS meeting, Vancouver, BC, Canada. (not barrier-free)
- Gaiser, P. et al. (2004), The WindSat space borne polarimetric microwave radiometer: sensor description and early orbit performance, Transactions Geoscience Remote Sensing, 42(11), 2347-2361.
- Meissner, T., L. Ricciardulli and F. J. Wentz (2010), The RSS WindSat version 7 all-weather wind vector product, paper presented at International Ocean Vector Winds Meeting, Barcelona, Spain. (not barrier-free)
- Meissner, T., L. Ricciardulli and F. J. Wentz (2010), Wind Measurements from Active and Passive Microwave Sensors: High Winds and Winds in Rain, paper presented at URSI-F Microwave Signatures Meeting 2010, Florence, Italy. (not barrier-free)
- Meissner, T. and F. J. Wentz (2009), Wind Vector Retrievals Under Rain With Passive Satellite Microwave Radiometers, Transactions Geoscience Remote Sensing, 47(9), 3065-3083. (not barrier-free)
- Zhang, L., et al., 2018, Comparison of wind speeds from spaceborne microwave radiometers with in situ observations and ECMWF data over the global ocean, Remote Sensing, 10(3), 425, http://doi.org/10.3390/rs10030425.
When using the data please cite as follows:
Wentz, F. J., L. Ricciardulli, C. Gentemann, T. Meissner, K. A. Hilburn, and J. Scott, 2013: Remote Sensing Systems Coriolis WindSat Daily Environmental Suite on 0.25 deg grid, Version 7.0.1. Remote Sensing Systems, Santa Rosa, CA. Available online at www.remss.com/missions/windsat. [Accessed from www.remss.com, last access date: July 27, 2020]. Downloaded in netCDF file format from the Integrated Climate Data Center (ICDC, icdc.cen.uni-hamburg.de) University of Hamburg, Hamburg, Germany.
In addition please add to the acknowledgements:
WindSat data are produced by Remote Sensing Systems and sponsored by the NASA Earth Science MEaSUREs DISCOVER Project and the NASA Earth Science Physical Oceanography Program. RSS WindSat data are available at www.remss.com.